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Amazon EMR vs Hadoop: What are the differences?
Developers describe Amazon EMR as "Distribute your data and processing across a Amazon EC2 instances using Hadoop". Amazon EMR is used in a variety of applications, including log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics. Customers launch millions of Amazon EMR clusters every year. On the other hand, Hadoop is detailed as "Open-source software for reliable, scalable, distributed computing". The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Amazon EMR can be classified as a tool in the "Big Data as a Service" category, while Hadoop is grouped under "Databases".
"On demand processing power" is the top reason why over 13 developers like Amazon EMR, while over 34 developers mention "Great ecosystem" as the leading cause for choosing Hadoop.
Hadoop is an open source tool with 9.27K GitHub stars and 5.78K GitHub forks. Here's a link to Hadoop's open source repository on GitHub.
According to the StackShare community, Hadoop has a broader approval, being mentioned in 237 company stacks & 127 developers stacks; compared to Amazon EMR, which is listed in 95 company stacks and 18 developer stacks.
Pros of Amazon EMR
- On demand processing power15
- Don't need to maintain Hadoop Cluster yourself12
- Hadoop Tools7
- Elastic6
- Backed by Amazon4
- Flexible3
- Economic - pay as you go, easy to use CLI and SDKs3
- Don't need a dedicated Ops group2
- Great support1
- Massive data handling1
Pros of Hadoop
- Great ecosystem38
- One stack to rule them all11
- Great load balancer4
- Amazon aws1
- Java syntax1